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Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts
Published on: January 29, 2018
A critical review of racial/ethnic variables in osteoporosis and bone density research
M S Megyesi1, L M Hunt, H Brody
1Joint POW/MIA Accounting Command, Central Identification Laboratory, 310 Worchester Ave Bldg 45, Hickam AFB, HI 96853-5530, USA. mary.megyesi@jpac.pacom.mil
Unlabelled:
Racial and ethnic variables are common in research on variation in bone density. This literature review describes some of the common flaws associated with the use of these variables and provides some suggestions for how bone density research may be able to better document and address skeletal health disparities.
Introduction:
Racial/ethnic differences in bone density have been commonly documented in the research literature. While effective identification of the specific factors underlying these trends might go a long way in informing treatment and screening for osteoporosis, this would require careful consideration of exactly what these variables are capturing. However, the basis and implications of what racial/ethnic variables represent have not carefully been examined in bone density research.
Methods:
For this paper, we systematically reviewed 55 articles that included bone density and race/ethnicity as key variables. Our analysis reveals that racial/ethnic terminology in these articles is highly variable, and discussion of how race/ethnicity is determined is often vague and idiosyncratic. Racial/ethnic variables are being used for a wide range of analytical purposes in statistical tests, which may not be appropriate for such a complex and poorly defined variable.
Results:
Many articles attribute racial/ethnic differences in bone mass/bone density to genetic causes, although few studies actually examine genetic data.
Conclusion:
This analysis indicates that more rigorous examination of what race/ethnicity actually captures, more careful definitions of group labels and the procedures for assigning them, and attention to the limitations of how such variables can reliably be used in data analyses is needed to help address the problems and issues outlined in this review.
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